Search Results for author: Takahiro Ishikawa

Found 3 papers, 1 papers with code

Lattice dynamics effects on finite-temperature stability of $R_{1-x}$Fe$_{x}$ ($R$ = Y, Ce, Nd, Sm, and Dy) alloys from first principles

no code implementations4 Feb 2021 Guangzong Xing, Takahiro Ishikawa, Yoshio Miura, Takashi Miyake, Terumasa Tadano

We report the effects of lattice dynamics on thermodynamic stability of binary $R_{1-x}$Fe$_x$ $(0<x<1)$ compounds ($R$: rare-earth elements, Y, Ce, Nd, Sm, and Dy) at finite temperature predicted by first-principles calculation based on density functional theory (DFT).

Materials Science Computational Physics

Evolutionary search for cobalt-rich compounds in the yttrium-cobalt-boron system

no code implementations3 Feb 2021 Takahiro Ishikawa, Taro Fukazawa, Guangzong Xing, Terumasa Tadano, Takashi Miyake

Modern high-performance permanent magnets are made from alloys of rare earth and transition metal elements, and large magnetization is achieved in the alloys with high concentration of transition metals.

Materials Science

ChainerRL: A Deep Reinforcement Learning Library

1 code implementation9 Dec 2019 Yasuhiro Fujita, Prabhat Nagarajan, Toshiki Kataoka, Takahiro Ishikawa

In this paper, we introduce ChainerRL, an open-source deep reinforcement learning (DRL) library built using Python and the Chainer deep learning framework.

reinforcement-learning Reinforcement Learning (RL)

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